%0 Journal Article
%T Image Edge Detection Based on Improved Artificial Fish-School Swarm Algorithm<br>基于改进人工鱼群算法的图像边缘检测①
%A CHU Xiao-Li
%A ZHU Ying
%A SHI Jun-Tao
%A <br>楚晓丽
%A 朱英
%A 石俊涛
%J 计算机系统应用
%D 2010
%I 
%X A method of image edge detection based on artificial fish swarm algorithm(AFSA)with chaos differential evolution algorithm(CDEA) is proposed in this paper. The method gets gradient matrix of grayscale image by first-order derivative, and search the maximum of image gradient with artificial fish. The detecting image edge could be achieved rapidly and accurately. The ability of search can be improved with adjustment factor in CDEA. It dynamically adjusts the vision, makes the fish jump out of the local extreme. The simulation shows that the proposed algorithm is feasible and effective.
%K artificial fish-school algorithm(AFSA)
%K chaos differential evolution algorithm(CDEA)
%K image edge detection
%K image gradient
%K image processing<br>人工鱼群算法
%K 混沌差分进化算子
%K 图像边缘检测
%K 图像梯度
%K 图像
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=6D6C089D9AEE6B4D30F91AB93E837983&yid=140ECF96957D60B2&vid=2A8D03AD8076A2E3&iid=5D311CA918CA9A03&sid=DABEF202280E7EF1&eid=5BC9492E1D772407&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=4